{"id":"W591557282","doi":"","title":"Improving Canadian Performance of SMA by Maximizing Best Practices","year":2005,"lang":"en","type":"article","venue":"","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Asphalt; Durability; Gradation; Engineering; SMA*; Context (archaeology); Aggregate (composite); Compaction; Forensic engineering; Civil engineering; Computer science; Geotechnical engineering; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028186,0.0006275794,0.0003702611,0.002497329,0.004456568,0.003215374,0.001678546,0.0004353116,0.00691071],"category_scores_gemma":[0.006288728,0.0002640029,0.0003068203,0.003618457,0.0005291197,0.001364906,0.001520294,0.0004172362,0.001292745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03738577,"about_ca_system_score_gemma":0.05057396,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8869166,"about_ca_topic_score_gemma":0.9698904,"domain_scores_codex":[0.9935496,0.0005381916,0.0001461546,0.0003480926,0.004392088,0.001025793],"domain_scores_gemma":[0.9939839,0.0001459536,0.0002049337,0.0003120934,0.004838662,0.0005144148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000514985,0.0009174736,0.06711546,0.0004995224,0.00008656896,0.0003761797,0.004735766,0.02721845,0.03213054,0.02353803,0.05617359,0.7866935],"study_design_scores_gemma":[0.0001192346,0.00150401,0.4207738,0.0005121257,0.0003043039,0.0007201895,0.01762677,0.04974416,0.07566229,0.006712833,0.4258742,0.0004460773],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5959402,0.001542587,0.01365908,0.003463996,0.00009162735,0.0004287081,0.002098427,0.001829476,0.3809459],"genre_scores_gemma":[0.9295464,0.001258776,0.03279266,0.0001857534,0.00001475045,0.00006845565,0.001129433,0.0002253892,0.03477829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1130834,"threshold_uncertainty_score":0.2712541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02416320114196776,"score_gpt":0.2495061934165663,"score_spread":0.2253429922745985,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}